Flexible production control method and system based on profiled steel continuous rolling process
By using a flexible production control method and system based on the continuous rolling process of special-shaped steel, the problem of declining quality of finished special-shaped steel products has been solved, and parameter adaptability and quality improvement have been achieved in the production process of special-shaped steel.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- WUXI GUANGXING DONGMAO TECH CO LTD
- Filing Date
- 2023-10-24
- Publication Date
- 2026-06-05
AI Technical Summary
In existing technologies, the process control parameters for continuous rolling of special-shaped steel are not well adapted to the special-shaped steel, resulting in a decline in the quality of finished products.
We provide a flexible production control method and system based on the continuous rolling process of special-shaped steel. The system obtains production orders through the user end, performs process optimization analysis on the flexible control platform, and achieves targeted control by combining dynamic monitoring and real-time parameter adjustment of the continuous rolling equipment terminal.
This improved the compatibility of production control parameters with shaped steel, thereby enhancing the quality of finished shaped steel products.
Smart Images
Figure CN117427997B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of data processing, and in particular to a flexible production control method and system based on the continuous rolling process of irregularly shaped steel. Background Technology
[0002] Special-shaped steel is a type of steel with complex and irregular cross-sections. Compared with ordinary steel, the production quantity of special-shaped steel is relatively small. Therefore, in the existing technology, the continuous rolling parameters for different special-shaped steels are mostly manually controlled during continuous rolling production. This results in poor compatibility between the control parameters and the special-shaped steel, leading to a decline in the quality of the finished special-shaped steel products.
[0003] Therefore, in the existing technology, the process control parameters for continuous rolling of special-shaped steel are not well adapted to the special-shaped steel, which leads to a decline in the quality of the finished special-shaped steel products. Summary of the Invention
[0004] This application provides a flexible production control method and system based on the continuous rolling process of special-shaped steel, which solves the technical problem that the control parameters of the continuous rolling process of special-shaped steel are not well adapted to the special-shaped steel, resulting in a decline in the quality of the finished special-shaped steel products.
[0005] This application provides a flexible production control method based on the continuous rolling process of special-shaped steel. The method is applied to a flexible production control system based on the continuous rolling process of special-shaped steel. The system includes a user terminal, a continuous rolling equipment terminal, and a flexible control platform terminal. The method includes: obtaining a first continuous rolling production order through the user terminal, wherein the first continuous rolling production order refers to an order with production requirements for the structural dimensions and continuous rolling quantity of a first special-shaped steel; the process optimization module in the flexible control platform terminal analyzes the structural dimensions in the first continuous rolling production order to obtain an optimal continuous rolling process decision; the continuous rolling production monitoring module dynamically monitors the production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision to obtain real-time monitoring parameters; adjusting the optimal continuous rolling process decision according to the real-time monitoring parameters to obtain a real-time continuous rolling process decision; and obtaining a second continuous rolling production order through the user terminal and scheduling production for the second continuous rolling production order based on the continuous rolling quantity.
[0006] This application also provides a flexible production control system based on the continuous rolling process of special-shaped steel. The system includes a user terminal, a continuous rolling equipment terminal, and a flexible control platform terminal. The system includes: an order demand acquisition module, used to acquire a first continuous rolling production order through the user terminal, wherein the first continuous rolling production order refers to an order with production requirements for the structural dimensions and continuous rolling quantity of a first special-shaped steel; a process decision module, used by the process optimization module in the flexible control platform terminal to analyze the structural dimensions in the first continuous rolling production order to obtain an optimal continuous rolling process decision; a monitoring parameter acquisition module, used to dynamically monitor the production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision through the continuous rolling production monitoring module to obtain real-time monitoring parameters; a decision adjustment module, used to adjust the optimal continuous rolling process decision according to the real-time monitoring parameters to obtain a real-time continuous rolling process decision; and a production scheduling module, used to acquire a second continuous rolling production order through the user terminal and schedule production for the second continuous rolling production order in conjunction with the continuous rolling quantity.
[0007] This application also provides an electronic device, including:
[0008] Memory, used to store executable instructions;
[0009] The processor, when executing executable instructions stored in the memory, implements the flexible production control method based on the continuous rolling process of irregular steel provided in this application.
[0010] This application provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the flexible production control method based on the continuous rolling process of irregularly shaped steel provided in this application.
[0011] This application proposes a flexible production control method and system based on the continuous rolling process of special-shaped steel. The system obtains the first continuous rolling production order through the user terminal. The process optimization module in the flexible control platform analyzes the structural dimensions in the first continuous rolling production order to obtain the optimal continuous rolling process decision. The continuous rolling production monitoring module dynamically monitors the production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision, obtaining real-time monitoring parameters. Based on the real-time monitoring parameters, the optimal continuous rolling process decision is adjusted to obtain the real-time continuous rolling process decision. The system then obtains the second continuous rolling production order through the user terminal to complete the order scheduling and production. This achieves targeted setting of continuous rolling process control parameters for special-shaped steel and user needs, realizing flexible production control of the continuous rolling process of special-shaped steel, improving the adaptability of production control parameters to special-shaped steel, and improving the quality of the finished special-shaped steel product. It solves the technical problem in existing technologies where the adaptability of continuous rolling process control parameters to special-shaped steel is weak, leading to a decline in the quality of the finished special-shaped steel product.
[0012] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description
[0013] To more clearly illustrate the technical solutions of the embodiments of this disclosure, the accompanying drawings of the embodiments of this disclosure will be briefly described below. Obviously, the drawings described below only relate to some embodiments of this disclosure and are not intended to limit this disclosure.
[0014] Figure 1 A flowchart illustrating the flexible production control method based on the continuous rolling process of irregularly shaped steel provided in this application embodiment;
[0015] Figure 2 A flowchart illustrating the output of the optimal continuous rolling process decision by the flexible production control method based on the continuous rolling process of irregular steel provided in the embodiments of this application.
[0016] Figure 3 A schematic diagram illustrating the process of real-time adjustment of rolling temperature in a flexible production control method based on continuous rolling of irregular steel provided in this application embodiment;
[0017] Figure 4 A schematic diagram of the system structure of the flexible production control method based on the continuous rolling process of special-shaped steel provided in the embodiments of this application;
[0018] Figure 5 This is a schematic diagram of the system electronic equipment for a flexible production control method based on the continuous rolling process of irregularly shaped steel provided in an embodiment of the present invention.
[0019] Explanation of reference numerals in the attached diagram: 11 Order demand acquisition module, 12 Process decision module, 13 Monitoring parameter acquisition module, 14 Decision adjustment module, 15 Production scheduling module, 31 Processor, 32 Memory, 33 Input device, 34 Output device. Detailed Implementation Example 1
[0020] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0021] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.
[0022] In the following description, the terms "first, second, third" are used merely to distinguish similar objects and do not represent a specific ordering of objects. It is understood that "first, second, third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.
[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only.
[0024] While this application makes various references to certain modules of the system according to embodiments of this application, any number of different modules may be used and run on user terminals and / or servers. These modules are merely illustrative, and different aspects of the system and method may use different modules.
[0025] This application uses flowcharts to illustrate the operations performed by the system according to embodiments of this application. It should be understood that the preceding or following operations are not necessarily performed in exact order. Instead, various steps can be processed in reverse order or simultaneously, as needed. Furthermore, other operations can be added to these processes, or one or more steps can be removed from them.
[0026] like Figure 1 As shown, this application provides a flexible production control method based on the continuous rolling process of special-shaped steel. The method is applied to a flexible production control system based on the continuous rolling process of special-shaped steel. The system includes a user terminal, a continuous rolling equipment terminal, and a flexible control platform terminal. The method includes:
[0027] The user terminal obtains the first continuous rolling production order, which refers to an order with the structural dimensions and continuous rolling quantity of the first special-shaped steel.
[0028] The process optimization module in the flexible control platform analyzes the structural dimensions in the first continuous rolling production order to obtain the optimal continuous rolling process decision.
[0029] The production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision is dynamically monitored by the continuous rolling production monitoring module to obtain real-time monitoring parameters.
[0030] Special-shaped steel is a type of steel with complex and irregular cross-sections. Since the production quantity of special-shaped steel is less than that of ordinary steel, in existing technologies, the continuous rolling parameters for different special-shaped steels are mostly manually controlled. This results in poor compatibility between the control parameters and the special-shaped steel, leading to a decline in the quality of the finished product. The user obtains the first continuous rolling production order through the user terminal, where the user fills in the continuous rolling production requirements. The first continuous rolling production order refers to an order with the structural dimensions and continuous rolling quantity of the first special-shaped steel. Subsequently, the process optimization module in the flexible control platform analyzes the structural dimensions in the first continuous rolling production order to obtain the optimal continuous rolling process decision. Furthermore, the continuous rolling production monitoring module dynamically monitors the production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision, obtaining real-time monitoring parameters.
[0031] like Figure 2 As shown, the method provided in this application embodiment further includes:
[0032] A set of control features is extracted from the production feature set of the assembled continuous rolling mill. The set of control features includes roll speed, rolling temperature, rolling pressure, and spraying duration.
[0033] The control feature set is used as the index to be optimized, and the first index parameter to be optimized is retrieved from the special-shaped steel continuous rolling database, and the first index parameter to be optimized corresponds to the first continuous rolling index.
[0034] The optimization results obtained by performing optimization analysis on the first index parameter to be optimized and the first continuous rolling index according to the preset optimization rules are added to the optimal continuous rolling process decision.
[0035] When obtaining the optimal continuous rolling process decision, a control feature set is extracted from the production feature set of the assembled continuous rolling equipment. This control feature set corresponds to the set of production control parameters for the continuous rolling equipment, including roll speed, rolling temperature, rolling pressure, and spray duration. Steel rolling spraying is a crucial step in the rolling mill operation process; it cools the roll surface by spraying cooling media through spray heads, reducing roll temperature, preventing overheating, reducing thermal stress, and extending roll life. Simultaneously, the spray heads can also spray cleaning agents to clean the roll surface and prevent impurities from adhering. Subsequently, the control feature set is used as the optimization index, and a first optimization index parameter is retrieved from the irregular steel continuous rolling database. This database records historical operating data and evaluation data for irregular steel continuous rolling, including specific index parameters (i.e., specific control parameters), corresponding detection index parameters, and the continuous rolling index corresponding to the optimization index parameter. The first optimization index parameter corresponds to a first continuous rolling index. The first continuous rolling index is the evaluation index corresponding to the first optimization index parameter. Finally, the optimization results obtained by performing optimization analysis on the first index parameter to be optimized and the first continuous rolling index according to the preset optimization rules are added to the optimal continuous rolling process decision.
[0036] The method provided in this application embodiment also includes:
[0037] The production feature set of the continuous rolling mill is constructed, and the production feature set includes the control feature set and the inherent feature set;
[0038] The inherent feature set includes roll body diameter, working diameter, roll pass depth, entry area, exit area, and section shrinkage.
[0039] The inherent feature set is used as a preset optimization constraint for optimization analysis and embedded in the preset optimization rule.
[0040] The production feature set of the continuous rolling mill is constructed, comprising the control feature set and the inherent feature set. The inherent feature set includes roll diameter, working diameter, roll pass depth, entry area, exit area, and section shrinkage. The inherent feature set is used as a preset optimization constraint for optimization analysis and embedded within the preset optimization rules.
[0041] The method provided in this application embodiment also includes:
[0042] Match the first continuous rolling detection parameters corresponding to the first index parameter to be optimized in the special-shaped steel continuous rolling database. The first continuous rolling detection parameters include the first continuous rolling high-quality rate, the first continuous rolling qualified rate, and the first continuous rolling straightening rate.
[0043] A preset continuous rolling evaluation function is introduced to analyze the first continuous rolling detection parameters to obtain the first continuous rolling index. The expression of the preset continuous rolling evaluation function is as follows:
[0044] ;
[0045] in, The first continuous rolling index, These are the first continuous rolling mill refined product rate, the first continuous rolling mill qualified rate, and the first continuous rolling mill straightening rate, respectively. a, b, and c are the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, respectively, and a+b+c=1.
[0046] The acquisition of the first continuous rolling index includes matching the first continuous rolling detection parameters corresponding to the first optimization index parameter in the special-shaped steel continuous rolling database. The first continuous rolling detection parameters are the detection index parameters corresponding to the first optimization index parameter. The first continuous rolling detection parameters include the first continuous rolling quality rate, the first continuous rolling pass rate, and the first continuous rolling straightening rate, which represent post-processing complexity. When straightening is required, the cooled special-shaped steel may have defects such as bending or twisting, requiring straightening treatment. Different defects have different post-processing complexities, and different complexities have corresponding complexity data. The aforementioned first continuous rolling quality rate, first continuous rolling pass rate, and first continuous rolling straightening rate parameters are all known evaluation data. Subsequently, a preset continuous rolling evaluation function is introduced to analyze the first continuous rolling detection parameters to obtain the first continuous rolling index. The expression of the preset continuous rolling evaluation function is:
[0047] ;
[0048] in, The first continuous rolling index, These are the first continuous rolling mill refined product rate, the first continuous rolling mill qualified rate, and the first continuous rolling mill straightening rate, respectively. a, b, and c are the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, respectively, and a + b + c = 1. Here, a, b, and c are weighting coefficients pre-set based on production needs or customer requirements.
[0049] The method provided in this application embodiment also includes:
[0050] The first set of parameters to be optimized includes the first roll speed, the first rolling temperature, the first rolling pressure, and the first spraying duration;
[0051] The first threshold of the roll speed, the second threshold of the rolling temperature, the third threshold of the rolling pressure, and the fourth threshold of the spraying duration are obtained sequentially.
[0052] Using the first threshold, the second threshold, the third threshold, and the fourth threshold as constraints, respectively, the first neighborhood of the first roll speed, the second neighborhood of the first rolling temperature, the third neighborhood of the first rolling pressure, and the fourth neighborhood of the first spray duration are obtained;
[0053] The first neighborhood index parameter is composed of a first neighborhood parameter randomly extracted from the first neighborhood, a second neighborhood parameter randomly extracted from the first neighborhood, a third neighborhood parameter randomly extracted from the first neighborhood, and a fourth neighborhood parameter randomly extracted from the fourth neighborhood.
[0054] Obtain the first neighborhood continuous rolling index corresponding to the first neighborhood index parameter;
[0055] When the first neighborhood continuous rolling index is greater than the first continuous rolling index, the first neighborhood index parameter is taken as the first optimization result.
[0056] Continue iterating and optimizing until a predetermined iteration threshold is reached, and then use the optimization result at that time as the optimization result.
[0057] The first parameter to be optimized includes a first roll speed, a first rolling temperature, a first rolling pressure, and a first spraying duration. Subsequently, a first threshold for the roll speed, a second threshold for the rolling temperature, a third threshold for the rolling pressure, and a fourth threshold for the spraying duration are sequentially obtained. These thresholds are all adjustment range thresholds for production parameters during the production process. Then, using the first, second, third, and fourth thresholds as constraints, a first neighborhood of the first roll speed, a second neighborhood of the first rolling temperature, a third neighborhood of the first rolling pressure, and a fourth neighborhood of the first spraying duration are obtained. The first, second, third, and fourth neighborhoods are all ranges of parameter adjacent to the corresponding parameters of the first parameter to be optimized; the specific neighborhood range is set through a pre-defined range. Subsequently, a first neighborhood parameter is formed by randomly extracting a first neighborhood parameter, a second neighborhood parameter, a third neighborhood parameter, and a fourth neighborhood parameter from the first neighborhood. Further, the first neighborhood continuous rolling index corresponding to the first neighborhood index parameter is obtained. When the first neighborhood continuous rolling index is greater than the first continuous rolling index, the first neighborhood index parameter is taken as the first optimization result. When the first neighborhood continuous rolling index is less than or equal to the first continuous rolling index, the first index parameter to be optimized is taken as the first optimization result. Iteration optimization continues until a predetermined iteration threshold is reached, and the optimization result at that time is taken as the optimization result. The predetermined iteration threshold is a specific iteration number threshold, which is a threshold for the number of optimizations preset before the optimization begins. The first neighborhood index parameter obtained in each optimization is different.
[0058] The method provided in this application embodiment also includes:
[0059] A first prediction layer is obtained by supervising learning the first training data composed of the first indicator parameter to be optimized and the first continuous rolling yield.
[0060] A second prediction layer is obtained by supervising learning the second training data composed of the first index parameter to be optimized and the first continuous rolling pass rate.
[0061] A third prediction layer is obtained by supervising learning the third training data composed of the first index parameter to be optimized and the first continuous rolling straightening rate.
[0062] A smart rolling prediction model is constructed by the first prediction layer, the second prediction layer, and the third prediction layer;
[0063] The first neighborhood continuous rolling index is obtained by analyzing the first neighborhood index parameters through the intelligent rolling prediction model combined with the preset continuous rolling evaluation function.
[0064] When obtaining the first neighborhood continuous rolling index based on the first neighborhood index parameters, a first prediction layer is obtained by supervised learning on the first training data composed of the first index parameters to be optimized and the first continuous rolling yield rate. A second prediction layer is obtained by supervised learning on the second training data composed of the first index parameters to be optimized and the first continuous rolling pass rate. A third prediction layer is obtained by supervised learning on the third training data composed of the first index parameters to be optimized and the first continuous rolling straightening rate. Specifically, when constructing the first prediction layer, supervised training of the neural network model is performed by obtaining the index parameters to be optimized and the corresponding continuous rolling yield rate data from the special-shaped steel continuous rolling database until the model outputs continuous rolling yield rate data that meets a preset accuracy rate, thus completing the model training and obtaining the first prediction layer. The acquisition methods for the second and third prediction layers differ from those for the first prediction layer only in the training data. Finally, an intelligent rolling prediction model is constructed from the first, second, and third prediction layers. By combining the intelligent rolling prediction model with the preset continuous rolling evaluation function, the first neighborhood index is obtained by analyzing the first neighborhood index parameters.
[0065] The optimal continuous rolling process decision is adjusted based on the real-time monitoring parameters to obtain the real-time continuous rolling process decision.
[0066] The user terminal obtains the second continuous rolling production order and schedules the production of the second continuous rolling production order based on the continuous rolling quantity.
[0067] The optimal continuous rolling process decision is adjusted based on the real-time monitoring parameters to obtain the real-time continuous rolling process decision. Finally, a second continuous rolling production order is obtained through the user terminal, and the second continuous rolling production order is scheduled for production based on the continuous rolling quantity. This achieves targeted setting of continuous rolling process control parameters for special-shaped steel and user needs, completes flexible production control of the special-shaped steel continuous rolling process, improves the adaptability of production control parameters to special-shaped steel, and improves the quality of finished special-shaped steel products.
[0068] like Figure 3 As shown, the method provided in this application embodiment further includes:
[0069] The real-time temperature parameters of the rolls in the continuous rolling mill are obtained by dynamically monitoring the temperature of the rolls using the first temperature sensor.
[0070] If the real-time temperature parameters of the rolls do not meet the preset roll temperature threshold, the rolling temperature is adjusted in real time.
[0071] The first temperature sensor dynamically monitors the temperature of the rolls in the continuous rolling mill to obtain real-time roll temperature parameters. During rolling, excessively high or low temperatures can cause the pre-formed steel material to adhere to the rolls, affecting the roll surface flatness and consequently the appearance quality of the subsequently rolled steel. The preset roll temperature threshold is based on a normal roll temperature value pre-set by technicians. If the real-time roll temperature parameters do not meet the preset roll temperature threshold, the rolling temperature is adjusted in real-time.
[0072] The method provided in this application embodiment also includes:
[0073] The second temperature sensor is used to dynamically monitor the temperature of the pre-shaped steel material after rolling to obtain the real-time temperature parameters of the material.
[0074] If the real-time temperature parameter of the material does not meet the preset material temperature threshold, the spraying duration is adjusted in real time.
[0075] The second temperature sensor dynamically monitors the temperature of the pre-formed special-shaped steel material after rolling. Since spray cooling is performed after rolling, the temperature after spraying is measured to obtain the real-time temperature parameters of the material. The preset material temperature threshold is based on a material temperature threshold pre-set by technicians. If the real-time material temperature parameters do not meet the preset material temperature threshold, the spraying time is adjusted in real time; for example, if the temperature is low, the spraying time can be appropriately reduced.
[0076] The technical solution provided by this invention involves obtaining a first continuous rolling production order through the user terminal. The process optimization module in the flexible control platform analyzes the structural dimensions in the first continuous rolling production order to obtain the optimal continuous rolling process decision. The continuous rolling production monitoring module dynamically monitors the production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision, obtaining real-time monitoring parameters. The optimal continuous rolling process decision is adjusted according to the real-time monitoring parameters to obtain a real-time continuous rolling process decision. A second continuous rolling production order is obtained through the user terminal to complete the order scheduling and production. This achieves targeted setting of continuous rolling process control parameters for special-shaped steel and user needs, completing flexible production control of the special-shaped steel continuous rolling process, improving the adaptability of production control parameters to special-shaped steel, and improving the quality of the finished special-shaped steel product. It solves the technical problem in the prior art where the adaptability of the continuous rolling process control parameters for special-shaped steel is weak, leading to a decline in the quality of the finished special-shaped steel product. Example 2
[0077] Based on the same inventive concept as the flexible production control method based on the continuous rolling process of special-shaped steel in the foregoing embodiments, this invention also provides a system for the flexible production control method based on the continuous rolling process of special-shaped steel. The system can be implemented in hardware and / or software, and is generally integrated into an electronic device to execute the method provided in any embodiment of this invention. For example... Figure 4 As shown, the system includes a user terminal, a continuous rolling mill terminal, and a flexible control platform terminal. The system includes:
[0078] The order demand acquisition module 11 is used to acquire the first continuous rolling production order through the user terminal. The first continuous rolling production order refers to an order with the structural dimensions and continuous rolling quantity of the first special-shaped steel.
[0079] Process decision module 12 is used by the process optimization module in the flexible control platform to analyze the structural dimensions in the first continuous rolling production order and obtain the optimal continuous rolling process decision.
[0080] The monitoring parameter acquisition module 13 is used to dynamically monitor the production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision through the continuous rolling production monitoring module, and obtain real-time monitoring parameters.
[0081] Decision adjustment module 14 is used to adjust the optimal continuous rolling process decision based on the real-time monitoring parameters to obtain the real-time continuous rolling process decision;
[0082] The production scheduling module 15 is used to obtain the second continuous rolling production order through the user terminal and schedule the production of the second continuous rolling production order in combination with the continuous rolling quantity.
[0083] Furthermore, the process decision module 12 is also used for:
[0084] A set of control features is extracted from the production feature set of the assembled continuous rolling mill. The set of control features includes roll speed, rolling temperature, rolling pressure, and spraying duration.
[0085] The control feature set is used as the index to be optimized, and the first index parameter to be optimized is retrieved from the special-shaped steel continuous rolling database, and the first index parameter to be optimized corresponds to the first continuous rolling index.
[0086] The optimization results obtained by performing optimization analysis on the first index parameter to be optimized and the first continuous rolling index according to the preset optimization rules are added to the optimal continuous rolling process decision.
[0087] Furthermore, the process decision module 12 is also used for:
[0088] The production feature set of the continuous rolling mill is constructed, and the production feature set includes the control feature set and the inherent feature set;
[0089] The inherent feature set includes roll body diameter, working diameter, roll pass depth, entry area, exit area, and section shrinkage.
[0090] The inherent feature set is used as a preset optimization constraint for optimization analysis and embedded in the preset optimization rule.
[0091] Furthermore, the process decision module 12 is also used for:
[0092] Match the first continuous rolling detection parameters corresponding to the first index parameter to be optimized in the special-shaped steel continuous rolling database. The first continuous rolling detection parameters include the first continuous rolling high-quality rate, the first continuous rolling qualified rate, and the first continuous rolling straightening rate.
[0093] A preset continuous rolling evaluation function is introduced to analyze the first continuous rolling detection parameters to obtain the first continuous rolling index. The expression of the preset continuous rolling evaluation function is as follows:
[0094] ;
[0095] in, The first continuous rolling index, These are the first continuous rolling mill refined product rate, the first continuous rolling mill qualified rate, and the first continuous rolling mill straightening rate, respectively. a, b, and c are the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, respectively, and a+b+c=1.
[0096] Furthermore, the process decision module 12 is also used for:
[0097] The first set of parameters to be optimized includes the first roll speed, the first rolling temperature, the first rolling pressure, and the first spraying duration;
[0098] The first threshold of the roll speed, the second threshold of the rolling temperature, the third threshold of the rolling pressure, and the fourth threshold of the spraying duration are obtained sequentially.
[0099] Using the first threshold, the second threshold, the third threshold, and the fourth threshold as constraints, respectively, the first neighborhood of the first roll speed, the second neighborhood of the first rolling temperature, the third neighborhood of the first rolling pressure, and the fourth neighborhood of the first spray duration are obtained;
[0100] The first neighborhood index parameter is composed of a first neighborhood parameter randomly extracted from the first neighborhood, a second neighborhood parameter randomly extracted from the first neighborhood, a third neighborhood parameter randomly extracted from the first neighborhood, and a fourth neighborhood parameter randomly extracted from the fourth neighborhood.
[0101] Obtain the first neighborhood continuous rolling index corresponding to the first neighborhood index parameter;
[0102] When the first neighborhood continuous rolling index is greater than the first continuous rolling index, the first neighborhood index parameter is taken as the first optimization result.
[0103] Continue iterating and optimizing until a predetermined iteration threshold is reached, and then use the optimization result at that time as the optimization result.
[0104] Furthermore, the process decision module 12 is also used for:
[0105] A first prediction layer is obtained by supervising learning the first training data composed of the first indicator parameter to be optimized and the first continuous rolling yield.
[0106] A second prediction layer is obtained by supervising learning the second training data composed of the first index parameter to be optimized and the first continuous rolling pass rate.
[0107] A third prediction layer is obtained by supervising learning the third training data composed of the first index parameter to be optimized and the first continuous rolling straightening rate.
[0108] A smart rolling prediction model is constructed by the first prediction layer, the second prediction layer, and the third prediction layer;
[0109] The first neighborhood continuous rolling index is obtained by analyzing the first neighborhood index parameters through the intelligent rolling prediction model combined with the preset continuous rolling evaluation function.
[0110] Furthermore, the decision adjustment module 14 is also used for:
[0111] The real-time temperature parameters of the rolls in the continuous rolling mill are obtained by dynamically monitoring the temperature of the rolls using the first temperature sensor.
[0112] If the real-time temperature parameters of the rolls do not meet the preset roll temperature threshold, the rolling temperature is adjusted in real time.
[0113] Furthermore, the decision adjustment module 14 is also used for:
[0114] The second temperature sensor is used to dynamically monitor the temperature of the pre-shaped steel material after rolling to obtain the real-time temperature parameters of the material.
[0115] If the real-time temperature parameter of the material does not meet the preset material temperature threshold, the spraying duration is adjusted in real time.
[0116] The various units and modules included are divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of this invention. Example 3
[0117] Figure 5 This is a schematic diagram of the structure of an electronic device provided in Embodiment 3 of the present invention, showing a block diagram of an exemplary electronic device suitable for implementing the embodiments of the present invention. Figure 5 The electronic device shown is merely an example and should not be construed as limiting the functionality or scope of the embodiments of the present invention. Figure 5 As shown, the electronic device includes a processor 31, a memory 32, an input device 33, and an output device 34; the number of processors 31 in the electronic device can be one or more. Figure 5 Taking a processor 31 as an example, the processor 31, memory 32, input device 33, and output device 34 in an electronic device can be connected via a bus or other means. Figure 5 Taking the example of a connection between China and Israel via a bus.
[0118] The memory 32, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the flexible production control method based on the continuous rolling process of special-shaped steel in this embodiment of the invention. The processor 31 executes various functional applications and data processing of the computer device by running the software programs, instructions, and modules stored in the memory 32, thereby realizing the aforementioned flexible production control method based on the continuous rolling process of special-shaped steel.
[0119] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.
Claims
1. A flexible production control method based on the continuous rolling process of irregularly shaped steel, characterized in that, The method is applied to a flexible production control system based on the continuous rolling process of special-shaped steel. The system includes a user terminal, a continuous rolling equipment terminal, and a flexible control platform terminal. The method includes: The user terminal obtains the first continuous rolling production order, which refers to an order with the structural dimensions and continuous rolling quantity of the first special-shaped steel. The process optimization module in the flexible control platform analyzes the structural dimensions in the first continuous rolling production order to obtain the optimal continuous rolling process decision. The production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision is dynamically monitored by the continuous rolling production monitoring module to obtain real-time monitoring parameters. The optimal continuous rolling process decision is adjusted based on the real-time monitoring parameters to obtain the real-time continuous rolling process decision. The user terminal obtains the second continuous rolling production order and schedules the production of the second continuous rolling production order based on the continuous rolling quantity. The flexible control platform has an embedded database of irregular steel continuous rolling mills. The process of obtaining the optimal continuous rolling process decision includes: A set of control features is extracted from the production feature set of the assembled continuous rolling mill. The set of control features includes roll speed, rolling temperature, rolling pressure, and spraying duration. The control feature set is used as the index to be optimized, and the first index parameter to be optimized is retrieved from the special-shaped steel continuous rolling database, and the first index parameter to be optimized corresponds to the first continuous rolling index. The optimization results obtained by performing optimization analysis on the first index parameter to be optimized and the first continuous rolling index according to the preset optimization rules are added to the optimal continuous rolling process decision. The step of adding the optimization results obtained by performing optimization analysis on the first index parameter to be optimized and the first continuous rolling index according to preset optimization rules into the optimal continuous rolling process decision includes: The production feature set of the continuous rolling mill is constructed, and the production feature set includes the control feature set and the inherent feature set; The inherent feature set includes roll body diameter, working diameter, roll pass depth, entry area, exit area, and section shrinkage. The inherent feature set is used as a preset optimization constraint for optimization analysis and embedded in the preset optimization rule.
2. The method according to claim 1, characterized in that, The first parameter to be optimized corresponds to the first continuous rolling index, including: Match the first continuous rolling detection parameters corresponding to the first index parameter to be optimized in the special-shaped steel continuous rolling database. The first continuous rolling detection parameters include the first continuous rolling high-quality rate, the first continuous rolling qualified rate, and the first continuous rolling straightening rate. A preset continuous rolling evaluation function is introduced to analyze the first continuous rolling detection parameters to obtain the first continuous rolling index. The expression of the preset continuous rolling evaluation function is as follows: ； in, The first continuous rolling index, , , These are the first continuous rolling mill refined product rate, the first continuous rolling mill qualified rate, and the first continuous rolling mill straightening rate, respectively. a, b, and c are the first weighting coefficient, the second weighting coefficient, and the third weighting coefficient, respectively, and a+b+c=1.
3. The method according to claim 2, characterized in that, The method further includes: The first set of parameters to be optimized includes the first roll speed, the first rolling temperature, the first rolling pressure, and the first spraying duration; The first threshold of the roll speed, the second threshold of the rolling temperature, the third threshold of the rolling pressure, and the fourth threshold of the spraying duration are obtained sequentially. Using the first threshold, the second threshold, the third threshold, and the fourth threshold as constraints, respectively, the first neighborhood of the first roll speed, the second neighborhood of the first rolling temperature, the third neighborhood of the first rolling pressure, and the fourth neighborhood of the first spray duration are obtained; The first neighborhood index parameter is composed of the first neighborhood parameter randomly extracted from the first neighborhood, the second neighborhood parameter randomly extracted from the second neighborhood, the third neighborhood parameter randomly extracted from the third neighborhood, and the fourth neighborhood parameter randomly extracted from the fourth neighborhood. Obtain the first neighborhood continuous rolling index corresponding to the first neighborhood index parameter; When the first neighborhood continuous rolling index is greater than the first continuous rolling index, the first neighborhood index parameter is taken as the first optimization result. Continue iterating and optimizing until a predetermined iteration threshold is reached, and then use the optimization result at that time as the optimization result.
4. The method according to claim 3, characterized in that, The step of obtaining the first neighborhood continuous rolling index corresponding to the first neighborhood index parameter includes: A first prediction layer is obtained by supervising learning the first training data composed of the first indicator parameter to be optimized and the first continuous rolling yield. A second prediction layer is obtained by supervising learning the second training data composed of the first index parameter to be optimized and the first continuous rolling pass rate. A third prediction layer is obtained by supervising learning the third training data composed of the first index parameter to be optimized and the first continuous rolling straightening rate. A smart rolling prediction model is constructed by the first prediction layer, the second prediction layer, and the third prediction layer; The first neighborhood continuous rolling index is obtained by analyzing the first neighborhood index parameters through the intelligent rolling prediction model combined with the preset continuous rolling evaluation function.
5. The method according to claim 1, characterized in that, The continuous rolling production monitoring module includes a first temperature sensor. The step of adjusting the optimal continuous rolling process decision based on the real-time monitoring parameters to obtain a real-time continuous rolling process decision includes: The real-time temperature parameters of the rolls in the continuous rolling mill are obtained by dynamically monitoring the temperature of the rolls using the first temperature sensor. If the real-time temperature parameters of the rolls do not meet the preset roll temperature threshold, the rolling temperature is adjusted in real time.
6. The method according to claim 5, characterized in that, The continuous rolling production monitoring module includes a second temperature sensor. The step of adjusting the optimal continuous rolling process decision based on the real-time monitoring parameters to obtain a real-time continuous rolling process decision includes: The second temperature sensor is used to dynamically monitor the temperature of the pre-shaped steel material after rolling to obtain the real-time temperature parameters of the material. If the real-time temperature parameter of the material does not meet the preset material temperature threshold, the spraying duration is adjusted in real time.
7. A flexible production control system based on the continuous rolling process of irregularly shaped steel, characterized in that, The system is used to perform the method as described in any one of claims 1-6, the system comprising a user terminal, a continuous rolling mill terminal, and a flexible control platform terminal, the system comprising: The order demand acquisition module is used to acquire the first continuous rolling production order through the user terminal. The first continuous rolling production order refers to an order with production requirements for the structural dimensions and continuous rolling quantity of the first special-shaped steel. The process decision module is used by the process optimization module in the flexible control platform to analyze the structural dimensions in the first continuous rolling production order and obtain the optimal continuous rolling process decision. The monitoring parameter acquisition module is used to dynamically monitor the production control process of the continuous rolling equipment terminal based on the optimal continuous rolling process decision through the continuous rolling production monitoring module, and obtain real-time monitoring parameters. The decision adjustment module is used to adjust the optimal continuous rolling process decision based on the real-time monitoring parameters to obtain the real-time continuous rolling process decision. The production scheduling module is used to obtain the second continuous rolling production order through the user terminal and schedule the production of the second continuous rolling production order in combination with the continuous rolling quantity.
8. An electronic device, characterized in that, The electronic device includes: Memory, used to store executable instructions; The processor, when executing executable instructions stored in the memory, implements the flexible production control method based on the continuous rolling process of irregular steel as described in any one of claims 1 to 6.